Understanding Two-Dimensional Lead Scoring

Lead scoring is an automated way of qualifying and segmenting leads (i.e. potential sales contacts) on your website. In other words, it’s a method shared by marketing and sales teams for determining the sales-readiness of leads. Having a lead-scoring system in place is the first step to quickly targeting and contacting leads closest to sale, further nurturing those not yet ready, and abandoning the rest.

In lead scoring, your site visitors are first scored according their activities on your website that reflect their engagement with your offer. This is then combined with points attributed based on their demographic data, such as geographical location, industry sector, or job title. This two-dimensional approach clearly reveals not just how well the leads engage with your business, but how well they fit into it, too.

These two dimensions are invaluable to avoid wasting time on leads (that have a high score, but no real interest in purchasing), and lost opportunities (on leads with a low score, but who are very interested in making a purchase). For example, a student working on his homework about your industry may spend hours on your website—reading your materials, watching your videos, and downloading brochures. This accrues him a very high score for engagement. But, in this two-dimensional approach to scoring, his demographic data wins him very few (or perhaps even negative) points for his fit into your business, meaning that his information is not passed to sales, so they can focus on real leads. To be processed by sales, leads must meet a certain score level in both dimensions.

Setting Up Lead Scoring Rules

Searching the internet, you are likely to find a list of 200+ scoring rules to consider. In this blog post we’ll provide you with the top 33 rules, proven to be effective for us on our main website: Kentico.com.

We use the powerful lead scoring feature of Kentico EMS as a key customer data and engagement analytics tool to segment site visitors and follow up with them accordingly. We use the two-dimensional system of scoring both engagement and fit to business on separate scales.

Explicit (Demographic) Scores Show How Well the Leads Fit Our Business

Explicit scores are highly dependent on data submitted to you by your site visitors. You may also acquire such data from 3rd party online directories of companies and business professionals. But our experience is that only a small portion of information gathered on the website will match (and can be paired with) the databases of these 3rd party services. Furthermore, even the successfully matched data is not always accurate.

So, the value of your explicit scoring is based on the richness of your website form fields, the willingness of visitors to complete them, and how honest they are when they do. However, the more fields there are in a form, the lower the response rate. So you have a balancing act to gather the most potent information in the smallest number of fields, having to make a compromise - amount of information vs. response rate.

In our case, we have only three mandatory fields - First name, Last Name, and E-mail - and two optional fields - Company and Phone.

Explicit Data - Demographic Scores

Rule Name

Points

Notes

Phone Number

10

This is an optional field; points are given for completion.

Company Name

5

This is an optional field; points are given for completion.

Company Email Address

5

E-mail is a mandatory field in all forms; points are given if email entered is not a free email address (as compared to our own list of known free email providers ) This might be the object of debate as many evaluators use free emails to download software in order to keep their company email SPAM-free.

Country

0-10

The majority of forms on our website don’t include this field; we use the geo-location service built in to Kentico CMS to select the country based on visitor IP address.

In the future, we could consider adding the following fields to enhance the scoring, but with an expected drop in conversion rate:

Visitor’s job title/type

Visitor’s company size/type

Industry of the visitor’s company

Available budget of the visitor’s company

Annual revenue of the visitor’s company

Implicit (Behavior Based) Scores Show How Well the Lead Engages with Your Business

The following table shows 25 scores that are based solely on the behavior of the lead or their source of traffic:

Implicit Data - Behaviour Scores

Implicit Data - Traffic Sources

Rule Name

Points

Notes

Traffic source - Direct

5

Anyone typing the URL of our website. We assume these visitors have previously heard of us by recommendation (WOM) or an offline campaign.

Traffic source - External Search

2

A person searching for a solution is considered to be more interested.

Traffic source - External Search inc. "kentico"

3

A person searching for a solution who already knows our brand is considered to be even more interested.

PPC Search Network Campaigns

5

PPC Campaigns in Search Networks bring people searching for a particular solution. We do these campaigns also for brand keywords. Wonder why?

Implicit Data - Behaviour at Website

Rule Name

Points

Notes

Number of Visits to Website

4

The same number of points are given for a visitor’s 2nd, 3rd, 4th and 5th visits to the website.

Number of Page Views

6

Number of page views reaches 10.

Number of Page Views

8

Number of page views reaches 20.

Number of Page Views

4

Number of page views reaches 30.

Number of Page Views

4

Number of page views reaches 40.

Visit to the "Purchase" Page

10

Visit page "Purchase"; activity is scored only once.

Visit to the "Order" Page

25

Visiting page "Order"; activity is scored only once.

Download of Assets

10

Download of any asset such as a whitepaper, eBook, Brochure, Report, etc. Each asset is scored extra; recurring download of same asset is not scored.

Internal Search

2

Any search done on our website. The idea behind this is that some visitors might skip browsing 10 additional pages and use the search feature instead. Also, this activity is the most suitable for sales to build highly personalized answers.

Purchase is not the exit page - In other words, visitor keeps browsing the site after seeing the pricing

Additional points for visits after period longer than X

Bad Implicit (Behavior Based) Scores

Although we currently don’t use any of them ourselves, a blog post on lead scoring rules wouldn’t be complete without mentioning negative scoring.

Here are some worth considering:

No website activity for a long period of time

Email unsubscribe

Not visiting a product or pricing page

Non-commercial interest

Visiting the Careers Area

Visiting the Press Area

Downloading the Free Edition

Creating Lead Scoring Labels

Clearly communicating a lead scoring system is crucial towards aligning the efforts of marketing & sales. Prior to setting up the scoring labels, there must be a common definition of all the terms used within the company, such as “visitor”, “lead”, “hot lead”, etc.

At Kentico, we are currently using three labels (groups) of leads:

Hot Lead – sales-ready leads that require a quick response from Sales

Warm Lead – leads with medium sales-readiness that need to be further nurtured

Cold Lead – leads with even lower sales-readiness that need nurturing from an earlier stage in the buying process

To be placed in a group, the lead must meet a certain score level in both dimensions – “engagement” and “fit to business”. The x axis of the following chart represents the level of engagement, while the y axis represents how well the lead fits the business.

The points required for each group that represent how well a lead fits our business (y axis) are below and have a maximum possible point level of 35:

To reach group A >= 30pts. To reach group B >= 20pts. To reach group C >=15pts. To reach group D < 15pts.

As you can see, we set up pretty strict rules in this dimension—a loss of more than 5 points removes a lead from group A. This ensures that a lead without a valid phone number—a loss of 10 points in our scoring system—could never be labeled a hot lead. Whereas a lead not supplying a company e-mail address, but only a free one—a loss of 5 points in our system rules—would still be considered a hot lead if all other rules are met.

The points required for each group that represent a lead’s engagement with our business (x axis) are below. There is no given maximum (as some of the activities can be scored repeatedly):

To reach group 1 >= 70pts. To reach group 2 >= 60pts. To reach group 3 >= 50pts. To reach group 4 < 50pts.

In practice, any emerging hot lead is contacted ASAP by the sales team, while warm leads are processed on the fly, being prioritized according to their scores. Simultaneously, warm and cold leads are nurtured by the Marketing Automation feature of Kentico EMS to become hot and sales-ready. But that’s a whole different story - see how to nurture leads using Marketing Automation.

Steps after the Successful Implementation of Lead Scoring

The implementation of lead scoring should initiate an ongoing and constructive discussion between marketing and sales that helps each better understand the needs of the other in achieving their common goals.

All implemented rules should be under constant analysis for relevance and effectiveness in terms of points assigned to them.

A deeper analysis of won and lost opportunities might be conducted on a regular basis to reveal weak points or false hypotheses employed in the initial implementation or latest iteration of the lead scoring system.

Petr is the Senior Business Analyst, responsible for the mapping and optimization of the sales funnel and revenue cycle leveraging the Kentico Customer Experience Management solution for online marketing activities.

Comments

Asm
commented on May 10, 2013

Thank you so much for sharing this precious info-rich post.

Petr Passinger
commented on Mar 27, 2013

Hi Pavel,thank you for your valuable comment! Length of stay was definitely one of the implicit scores that we initially considered, so this leads me to decision to go back to this post in couple of days and enrich it with the list of considered implicit scores (as I listed only those explicit ones that we considered). Thanks again!

Pavel
commented on Mar 27, 2013

I would suggest to add "time spent on web" rule to the list of implicit rules.